/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package org.apache.spark.sql.execution

import org.apache.spark.sql.{DataFrame, Dataset, Row, SparkSession}
import org.apache.spark.sql.catalyst.encoders.RowEncoder
import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan

/** Query execution that skips re-analysis and optimize. */
class AlreadyOptimizedExecution(
    session: SparkSession,
    plan: LogicalPlan) extends QueryExecution(session, plan) {
  override lazy val analyzed: LogicalPlan = plan
  override lazy val optimizedPlan: LogicalPlan = plan
}

object AlreadyOptimized {
  def dataFrame(sparkSession: SparkSession, optimized: LogicalPlan): DataFrame = {
    val qe = new AlreadyOptimizedExecution(sparkSession, optimized)
    new Dataset[Row](qe, RowEncoder(qe.analyzed.schema))
  }
}
